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Lawyers keep the gates of public justice institutions, particularly through their roles in formal procedures like hearings and trials. Yet, it is not clear what lawyers do in such quintessentially legal settings: conclusions from past research are bedeviled by a lack of clear theory and inconsistencies in research design. Conceptualizing litigation work in terms of professional expertise, I conduct a theoretically grounded synthesis of the findings of extant studies of lawyers’ impact on civil case outcomes.

The meaning of objectivity in any specific setting reflects historically situated understandings of both science and self. Recently, various scientific fields have confronted growing mistrust about the replicability of findings, and statistical techniques have been deployed to articulate a “crisis of false positives.” In response, epistemic activists have invoked a decidedly economic understanding of scientists’ selves. This has prompted a scientific social movement of proposed reforms, including regulating disclosure of “backstage” research details and enhancing incentives for replication.

Researchers studying income inequality, economic segregation, and other subjects must often rely on grouped data—that is, data in which thousands or millions of observations have been reduced to counts of units by specified income brackets.

As Michael Schultz notes in his very interesting paper (this volume, pp. 52–87), standard model selection criteria, such as the Akaike information criterion (AIC; Akaike 1974), the Bayesian information criterion (BIC; Schwarz 1978), and the minimum description length principle (MDL; Rissanen 1978), are purely empirical criteria in the sense that the score a model receives does not depend on how well the model coheres with background theory. This is unsatisfying because we would like our models to be theoretically plausible, not just empirically successful.

Conventional model selection evaluates models on their ability to represent data accurately, ignoring their dependence on theoretical and methodological assumptions. Drawing on the concept of underdetermination from the philosophy of science, the author argues that uncritical use of methodological assumptions can pose a problem for effective inference. By ignoring the plausibility of assumptions, existing techniques select models that are poor representations of theory and are thus suboptimal for inference.

Despite improved access in expanded postsecondary systems, the great majority of bachelor’s degree graduates are taking considerably longer than the allotted four years to complete their four-year degrees. Taking longer to finish one’s BA has become so pervasive in the United States that it has become the norm for official statistics released by the Department of Education to report graduation rates across a six-year window.

Cross-national empirical research about the link between income inequality and population health produces conflicting conclusions. We address these mixed findings by examining the degree to which the income inequality and health relationship varies with economic development. We estimate fixed-effects models with different measures of income inequality and population health. Results suggest that development moderates the association between inequality and two measures of population health. Our findings produce two generalizations.

Previous research shows that married and cohabiting individuals are happier and enjoy greater levels of psychological well-being than single individuals. However, most of this research relies on data from intraracial—mostly white—couples, and less is known about the emotional health outcomes of individuals in interracial partnerships. This study uses fixed-effects regression to examine depressive symptoms among those transitioning into intraracial and interracial relationships in the National Longitudinal Study of Adolescent to Adult Health.